From 0832cdd44335253393bc2345c5959f9214a9065a Mon Sep 17 00:00:00 2001 From: Ines Montani Date: Mon, 10 Aug 2020 00:46:32 +0200 Subject: [PATCH] Fix formatting [ci skip] --- website/docs/api/architectures.md | 24 +++++++++++------------- 1 file changed, 11 insertions(+), 13 deletions(-) diff --git a/website/docs/api/architectures.md b/website/docs/api/architectures.md index 8b07102ce..c79551761 100644 --- a/website/docs/api/architectures.md +++ b/website/docs/api/architectures.md @@ -525,12 +525,11 @@ A neural network model where token vectors are calculated using a CNN. The vectors are mean pooled and used as features in a feed-forward network. This architecture is usually less accurate than the ensemble, but runs faster. -| Name | Type | Description | -| --------------------------- | ------------------------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `exclusive_classes` | bool | Whether or not categories are mutually exclusive. | -| `tok2vec` | [`Model`](https://thinc.ai/docs/api-model) | The [`tok2vec`](#tok2vec) layer of the model. | -| `nO` | int | Output dimension, determined by the number of different labels. If not set, the the [`TextCategorizer`](/api/textcategorizer) component will set it when | -| `begin_training` is called. | +| Name | Type | Description | +| ------------------- | ------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | +| `exclusive_classes` | bool | Whether or not categories are mutually exclusive. | +| `tok2vec` | [`Model`](https://thinc.ai/docs/api-model) | The [`tok2vec`](#tok2vec) layer of the model. | +| `nO` | int | Output dimension, determined by the number of different labels. If not set, the the [`TextCategorizer`](/api/textcategorizer) component will set it when `begin_training` is called. | ### spacy.TextCatBOW.v1 {#TextCatBOW} @@ -548,13 +547,12 @@ architecture is usually less accurate than the ensemble, but runs faster. An ngram "bag-of-words" model. This architecture should run much faster than the others, but may not be as accurate, especially if texts are short. -| Name | Type | Description | -| --------------------------- | ----- | -------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `exclusive_classes` | bool | Whether or not categories are mutually exclusive. | -| `ngram_size` | int | Determines the maximum length of the n-grams in the BOW model. For instance, `ngram_size=3`would give unigram, trigram and bigram features. | -| `no_output_layer` | float | Whether or not to add an output layer to the model (`Softmax` activation if `exclusive_classes=True`, else `Logistic`. | -| `nO` | int | Output dimension, determined by the number of different labels. If not set, the the [`TextCategorizer`](/api/textcategorizer) component will set it when | -| `begin_training` is called. | +| Name | Type | Description | +| ------------------- | ----- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | +| `exclusive_classes` | bool | Whether or not categories are mutually exclusive. | +| `ngram_size` | int | Determines the maximum length of the n-grams in the BOW model. For instance, `ngram_size=3`would give unigram, trigram and bigram features. | +| `no_output_layer` | float | Whether or not to add an output layer to the model (`Softmax` activation if `exclusive_classes=True`, else `Logistic`. | +| `nO` | int | Output dimension, determined by the number of different labels. If not set, the the [`TextCategorizer`](/api/textcategorizer) component will set it when `begin_training` is called. |